2010 Simulated Car Racing Championship @ CIG-2010

The 2010 Simulated Car Racing
Championship @ CIG-2010
Daniele Loiacono, Luigi Cardamone,
Martin V. Butz, and Pier Luca Lanzi

2010 Simulated Car Racing Championship @ CIG-2010

2

2010 Simulated Car Racing Championship
9 races during 3 conferences

Develop a driver for TORCS
(hand-coded, learned, evolved, …)

Drivers will be awarded based on their score
in each conference competition

At the end, the team with highest overall score
wins the championship


The 2010 Simulated Car Racing Championship

CIG-2010
Copenhagen, August 18–21
Dusty Leg
GECCO-2010 Winner: ???
Portland , July 7-11
American Leg
Winner: Autopia

WCCI-2010
Barcelona, July 18-23
Formula Leg
Winner: Jorge Muñoz


4

What is the structure of a race?

Three stages: warm up, qualifiers, actual race

During warm-up, each driver can explore the
track and learn something useful

During qualifiers, each driver races alone against
the clock (the best 8 drivers move to the race)

During the race all the drivers race together


What’s new?

If everything seems under control, you're not going fast enough
— Mario Andretti
 Warm-up stage
Before qualifying stage, competitors have 100000 game
ticks to race on the track
Allows track learning and optimization of parameters
 Noisy sensors
Track sensors and opponent sensors are affected by a
Gaussian noise (standard deviation equal to 10% of the
readings)
 Extended sensor model
Focus sensors
Z position and speed
Direction of track sensors fully customizable
Added clutch control and focus command


The Open Racing Car Simulator

 TORCS is a state of the art open source simulator written in C++

 Main features
Sophisticated dynamics
Provided with several
cars, tracks, and
controllers
Active community of
users and developers
Easy to develop your
own controller

 OS Support
Linux: binaries and building from sources
Windows: binaries and “limited” bulding from sources support
OSX: legacy binaries and no building from sources support 


The Open Racing Car Simulator
& the Competition Software

TORCS TORCS
PATCH

BOT BOT BOT SBOT SBOT SBOT

 The competition server
UDP UDP UDP
 Separates the bots from TORCS
 Build a well-defined sensor model
 Works in real-time BOT BOT BOT


Sensors and actuators

 Rangefinders for edges on the track and opponents
 Speed, RPM, fuel, damage, angle with track, distance race, position
on track, etc.

 Six effectors: steering wheel [-1,+1], gas pedal [0, +1], brake
pedal [0,+1], gearbox {-1,0,1,2,3,4,5,6}, clutch [0,+1], focus
direction

The competitors

 Five entries in the second leg
AUTOPIA, Madrid and Granada
J. Muñoz, Carlos III University of Madrid
S.Pohl, J. Quadflieg and T. Delbrügger, TU Dortmund
Joseph Alton, University of Birmingham
Timothy Alford (Xiaodong Li), RMIT University, Melbourne
Neil Clarke, University of Birmingham

 Two more entries from the 2009 championship
COBOSTAR (T. Lönneker & M.V. Butz, University of
Würzburg)
POLIMI (Cardamone, Politecnico di Milano)


AUTOPIA

Industrial Computer Science Department.
Centro de Automática y Robótica
Consejo Superior de Investigaciones Científicas
Madrid, Spain
Contact:E. Onieva (enrique.onieva@car.upm-csic.es)

AUTOPIA

 Fuzzy Architecture based on three basic modules for gear,
steering and speed control
optimized with a genetic algorithm

 Learning in the warm-up stage:
Maintain a vector with as many real values as tracklength
in meters.
Vector initialized to 1.0
If the vehicle goes out of the track or suffers damage
then multiply vector positions from 250 meters before the
current position by 0.95.

 During the race the vector is multiplied by F to make the
driver more cautious in function of the damage:
F=1-0.02*round(damage/1000)


Mr Racer

Susanna Pohl, Jan Quadflieg and Tim Delbrügger
TU Dortmund


Mr. Racer

 Save the model after warm-up, use it during
qualifying and the race

 The track model is built using a classifier

 Use the model to derive a plan consisting of
target speeds and a racing line

 Unfortunately the noisy completely
breaks the classifier 


Jorge Muñoz

Department of Computer Science
Carlos III University of Madrid


Jorge Muñoz

 Build a model of the track during the warm-up stage.

 Two neural networks to predict the trajectory using the track
model. Two neural networks to predict the target speed
given the model of the track and the current car position

 The four neural networks are trained with backpropagation
using data retrieved from a human player

 Learning during the warm-up:
The car remember where it goes out of the car or drives
far form the trajectory and in the next laps goes slower in
those points
The car remember where it follows the trajectory perfectly
and tries to go faster in the next laps.


Joseph Alton

Joseph Alton


Joseph Alton

 Scripted controller

 During warm-up the controller drives with a fixed speed of
60 km/h
 During this time for each segment (meter) of the track, the
turns are recorded and mapped to a speed.
 The speeds are as follows:

Type Value Speed ( km/h)
Sharp turn > Absolute 0.1 60
Turn > Absolute 0.05 100
Straight 200

 Noise filtering is done through having multiple sensors at the
same position


Timothy Alford (supervised by Xiaodong Li)
RMIT University, Melbourne, Victoria


Tim Alford

 All components of the car are controlled by Fuzzy Logic
(excluding gears and recovery )
 Recovery, Gears are controlled with simple rules
 GA is exploited in the Warm-up

Fuzzy system
Action object
Y
Gears

Sensors on track
?

N Action object
Recovery


Timothy Alford (supervised by Xiaodong Li)
Neil Clarke
RMIT University, Melbourne, Victoria
University of Birmingham

Neil Clarke

 Controller based on a Feed Forward Multi Layer Neural
Network

 Imitation Leaning

 Trained using the human data provided by the author

 Very simple policy for the opponents


COBOSTAR

Thies Lönneker and Martin V. Butz
University of Würzburg

http://www.coboslab.psychologie.uni-wuerzburg.de

COBOSTAR

 One of the best controller of the 2009 Championship

 Parameterized controller optimized with CMA-ES

 Dynamically saves crash points


CIG-2008 Champ

Luigi Cardamone
Politecnico di Milano


Luigi Cardamone

 Winner of the CIG-2008 Car Simulated Competition

 The controller is based on a neural network evolved with
NEAT

 Very simple policy for overtaking


Scoring process: Warm-up Qualifying

 Scoring process involves three dirt tracks:
Dirt-1
Olethros-Dirt
Rocky

 Only the track Dirt-1 is provided with TORCS distribution:
Olethros-Dirt was created adding the sand to the original
track Olethros
Rocky is an evolved track

 Each controller raced for 100000 game ticks in the warm-up
stage and then its performance is computed in the qualifying
stage as the distance covered within 10000 game ticks


Dirt-1


Qualifying: Dirt-1

Timothy Alford 2291,56

Neil Clarke 5696,28

MR. Racer 4168,25

COBOSTAR 5218,73

Cardamone 5340,37

Joseph Alton 2665,89

Jorge Muñoz 4851,54

Autopia 6125,74

0 1000 2000 3000 4000 5000 6000 7000


Olethros-Dirt


Qualifying: Olethros-Dirt


Neil Clarke 2135,18

MR. Racer 2352,1

COBOSTAR 6285,36

Cardamone 5024,56

Joseph Alton 0


Autopia 6988,33

0 1000 2000 3000 4000 5000 6000 7000 8000


Rocky


Qualifying: Rocky


Neil Clarke 2261,45

MR. Racer 2736,39

COBOSTAR 6409,76

Cardamone 5881,37

Joseph Alton 0


Autopia 6177,81

0 1000 2000 3000 4000 5000 6000 7000


Qualifying summary

Dirt-1 Olethros-dirt Rocky Total
Autopia
10 10 8 28
Cardamone
5 8 10 23
COBOSTAR
6 6 6 18
Neil
8 2 3 13
Mr. Racer
4 3 5 12
Tim
3 4 4 11
Jorge Muñoz
1 5 2 8
Joseph Alton*
2 1 1 4

Joseph Alton was disqualified from the race as crashes in 2 over 3 tracks


What about qualifying?

AUTOPIA is the fastest driver
Also, Cardamone (a very old driver ) did very well

For some drivers noise seems to affect significantly the
performance

However, some controllers are able to reach almost the same
performance even with noise

How much does noise affect the
performance?


Dirt-1 with and without noise

1707,26
Timothy Alford
2291,56

6204,14
Neil Clarke
5696,28

5097,69
MR. Racer
4168,25

5380,04
COBOSTAR
5218,73

5404,24
Cardamone
5340,37

2666,12
Joseph Alton
2665,89

4966,6
Jorge Muñoz
4851,54

6201,71
Autopia
6125,74

0 1000 2000 3000 4000 5000 6000 7000

NO-NOISY NOISY


43

Three Tracks

For each track we run 7 races
with different starting grids

Each race is scored using the F1 point system
(10 to first, 8 to second, 6 to third, …)

Two points to the controller with lesser damage

Two points for the fastest lap of the race


Race: Dirt-1

Competitor Score
Cardamone 10

Autopia 8

COBOSTAR 8

Neil 7

Jorge Muñoz 4

Tim 4

Mr. Racer 3


Race: Olethros-dirt

Competitor Score
Autopia
12

COBOSTAR
8

Cardamone
6

Tim
6

Neil
5

Mr. Racer
4

Jorge Muñoz
2


Race: Rocky

Competitor Score
COBOSTAR
8

Cardamone
8

Mr. Racer
8

Jorge Muñoz
6

Autopia
5

Neil
4

Tim
3


Final Results

Competitor Dirt-1 Ole-Dirt Rocky Total

Autopia 8 12 5 25

Cardamone 10 6 8 24

COBOSTAR 8 8 8 24

Neil 7 5 4 16

Mr. Racer 3 4 8 15

Tim 4 6 3 13

Jorge Muñoz 4 2 6 12


Final Standings
Competitor GECCO WCCI CIG Total
AUTOPIA 34 24 25 83
COBOSTAR 14 28 24 66
Jorge Muñoz 22.5 28 12 62.5
Cardamone 16 16 24 56
Mr. Racer 16 9 15 40
Joseph Alton 15.5 11 - 26.5
Tim Alford - 10 13 23
Neil Clarke - - 16 16


The 2010 Simulated Car Racing Championship

CIG-2010
Copenhagen, August 18–21
Dusty Leg
GECCO-2010 Winner: Autopia
Portland , July 7-11
American Leg
Winner: Autopia

WCCI-2010
Barcelona, July 18-23
Formula Leg
Winner: Jorge Muñoz


Analysis of results

Competitor GECCO WCCI CIG
AUTOPIA 34 24 25
COBOSTAR 14 28 24
Jorge Muñoz 22.5 28 12
Cardamone 16 16 24
Mr. Racer 16 9 15
Joseph Alton 15.5 11 -
Tim Alford - 10 13
Neil Clarke - - 16


Analysis of results

GECCO WCCI CIG
1
2
3 AUTOPIA
COBOSTAR
4 Jorge Muñoz
Cardamone
5
Mr. Racer

6
7
8


What about new challenges?

 Noisy sensors
Addressed by almost all the competitors
For most of the approaches is critical only for opponent
management
Still an open problem

 Warm-up stage
Addressed by almost all the competitors
Simple on-line adaptation (e.g., list of crash points
implemented in COBOSTAR) still very competitive
We expect big improvements in this task in the future

 Custom Rangefinders Setup and Clutch Control


Conclusions

 Car Racing Community
Overall 6 competitors entered the competition (last year
we got 11 entries)
Almost the same authors in the first positions
New competitors enter for a while and leave
 Do not be scared 
The source of entries will be available on-line
A lot of opportunities to improve the current controllers


2010 Simulated Car Racing Championship @ CIG-2010

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